JournalTOCs

British Journal of Mathematical and Statistical Psychology
Journal Prestige (SJR): 3.074

Citation Impact (citeScore): 5
Number of Followers: 18

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ISSN (Print) 0007-1102 - ISSN (Online) 2044-8317
Published by British Psychological Society

[10 journals]

Data‐driven Q‐matrix validation using a residual‐based statistic in
cognitive diagnostic assessment
- Authors: Xiaofeng Yu; Ying Cheng
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page 145-179, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12191
  Issue No: Vol. 73, No. S1 (2020)
Bayesian power equivalence in latent growth curve models
- Authors: Angelika M. Stefan; Timo Oertzen
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page 180-193, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12193
  Issue No: Vol. 73, No. S1 (2020)
Marginalized maximum a posteriori estimation for the four‐parameter
logistic model under a mixture modelling framework
- Authors: Xiangbin Meng; Gongjun Xu, Jiwei Zhang, Jian Tao
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page 51-82, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12185
  Issue No: Vol. 73, No. S1 (2020)
Point‐biserial correlation: Interval estimation, hypothesis testing,
meta‐analysis, and sample size determination
- Authors: Douglas G. Bonett
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page 113-144, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12189
  Issue No: Vol. 73, No. S1 (2020)
The danger of conflating level‐specific effects of control variables
when primary interest lies in level‐2 effects
- Authors: Jason D. Rights; Kristopher J. Preacher, David A. Cole
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page 194-211, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12194
  Issue No: Vol. 73, No. S1 (2020)
Confidence interval‐based sample size determination formulas and some
mathematical properties for hierarchical data
- Authors: Satoshi Usami
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page 1-31, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12181
  Issue No: Vol. 73, No. S1 (2020)
Revisiting dispersion in count data item response theory models: The
Conway–Maxwell–Poisson counts model
- Authors: Boris Forthmann; Daniela Gühne, Philipp Doebler
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page 32-50, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12184
  Issue No: Vol. 73, No. S1 (2020)
A hierarchical latent response model for inferences about examinee
engagement in terms of guessing and item‐level non‐response
- Authors: Esther Ulitzsch; Matthias Davier, Steffi Pohl
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page 83-112, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12188
  Issue No: Vol. 73, No. S1 (2020)
Issue Information
- Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue S1, Page i-iv, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-25T12:54:07-08:00
  DOI: 10.1111/bmsp.12226
  Issue No: Vol. 73, No. S1 (2020)
Modelling monotonic effects of ordinal predictors in Bayesian regression
models
- Authors: Paul‐Christian Bürkner; Emmanuel Charpentier
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 420-451, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12195
  Issue No: Vol. 73, No. 3 (2020)
Modelling inter‐individual differences in latent within‐person
variation: The confirmatory factor level variability model
- Authors: Steffen Nestler
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 452-473, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12196
  Issue No: Vol. 73, No. 3 (2020)
A new quantile estimator with weights based on a subsampling approach
- Authors: Gözde Navruz; A. Fırat Özdemir
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 506-521, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12198
  Issue No: Vol. 73, No. 3 (2020)
Combining diversity and dispersion criteria for anticlustering: A
bicriterion approach
- Authors: Michael J. Brusco; J. Dennis Cradit, Douglas Steinley
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 375-396, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12186
  Issue No: Vol. 73, No. 3 (2020)
The use of item scores and response times to detect examinees who may have
benefited from item preknowledge
- Authors: Sandip Sinharay; Matthew S. Johnson
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 397-419, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12187
  Issue No: Vol. 73, No. 3 (2020)
D‐optimal design for the Rasch counts model with multiple binary
predictors
- Authors: Ulrike Graßhoff; Heinz Holling, Rainer Schwabe
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 541-555, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12204
  Issue No: Vol. 73, No. 3 (2020)
A latent topic model with Markov transition for process data
- Authors: Haochen Xu; Guanhua Fang, Zhiliang Ying
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 474-505, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12197
  Issue No: Vol. 73, No. 3 (2020)
Curiosity‐driven recommendation strategy for adaptive learning via
deep reinforcement learning
- Authors: Ruijian Han; Kani Chen, Chunxi Tan
  Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 522-540, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12199
  Issue No: Vol. 73, No. 3 (2020)
Issue Information
- Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page i-iv, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12178
  Issue No: Vol. 73, No. 3 (2020)
Corrigendum
- Abstract: British Journal of Mathematical and Statistical Psychology, Volume 73, Issue 3, Page 556-556, November 2020.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-10T11:15:17-08:00
  DOI: 10.1111/bmsp.12225
  Issue No: Vol. 73, No. 3 (2020)
Accounting for individual differences in speed in the discretized signed
residual time model
- Authors: Jesper Tijmstra; Maria Bolsinova
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-12-22T05:39:31-08:00
  DOI: 10.1111/bmsp.12223
A semiparametric approach for item response function estimation to detect
item misfit
- Authors: Carmen Köhler; Alexander Robitzsch, Katharina Fährmann, Matthias Davier, Johannes Hartig
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-12-17T10:02:05-08:00
  DOI: 10.1111/bmsp.12224
Notes on attribution functions
- Authors: Xun Ge; Shou Lin
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-12-13T05:42:43-08:00
  DOI: 10.1111/bmsp.12220
Random effects and extended generalized partial credit models
- Authors: David J. Hessen
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-12-10T10:39:33-08:00
  DOI: 10.1111/bmsp.12213
Balancing fit and parsimony to improve Q‐matrix validation
- Authors: Pablo Nájera; Miguel A. Sorrel, Jimmy Torre, Francisco José Abad
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-24T01:58:01-08:00
  DOI: 10.1111/bmsp.12228
The impacts of ignoring individual mobility across clusters in estimating
a piecewise growth model
- Authors: Audrey J. Leroux; Christopher J. Cappelli, David R. J. Fikis
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-24T01:57:23-08:00
  DOI: 10.1111/bmsp.12229
Accounting for auto‐dependency in binary dyadic time series data: A
comparison of model‐ and permutation‐based approaches for testing
pairwise associations
- Authors: Nadja Bodner; Francis Tuerlinckx, Guy Bosmans, Eva Ceulemans
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-22T11:19:57-08:00
  DOI: 10.1111/bmsp.12222
Relating latent class membership to external variables: An overview
- Authors: Zsuzsa Bakk; Jouni Kuha
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-11-16T10:18:27-08:00
  DOI: 10.1111/bmsp.12227
Gaussian variational estimation for multidimensional item response theory
- Authors: April E. Cho; Chun Wang, Xue Zhang, Gongjun Xu
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-10-16T12:00:00-07:00
  DOI: 10.1111/bmsp.12219
Causal graphical views of fixed effects and random effects models
- Authors: Yongnam Kim; Peter M. Steiner
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-10-15T12:00:00-07:00
  DOI: 10.1111/bmsp.12217
Maximum information per time unit designs for continuous online item
calibration
- Authors: Yinhong He; Ping Chen, Yong Li
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-10-12T11:39:23-07:00
  DOI: 10.1111/bmsp.12221
A close‐up comparison of the misclassification error distance and the
adjusted Rand index for external clustering evaluation
- Authors: José E. Chacón
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-10-08T11:40:29-07:00
  DOI: 10.1111/bmsp.12212
Robust Bayesian growth curve modelling using conditional medians
- Authors: Xin Tong; Tonghao Zhang, Jianhui Zhou
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-09-14T02:59:56-07:00
  DOI: 10.1111/bmsp.12216
Semi‐automated Rasch analysis using in‐plus‐out‐of‐questionnaire
log likelihood
- Authors: Feri Wijayanto; Karlien Mul, Perry Groot, Baziel G.M. van Engelen, Tom Heskes
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-08-28T07:35:09-07:00
  DOI: 10.1111/bmsp.12218
A note on computing Louis’ observed information matrix identity for IRT
and cognitive diagnostic models
- Authors: Chen‐Wei Liu; Robert Philip Chalmers
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-08-05T10:59:22-07:00
  DOI: 10.1111/bmsp.12207
The problem of measurement bias in comparing selected subgroups
- Authors: Jorge L. Mendoza; Seunghoo Lee, Dustin Fife
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-07-30T04:26:29-07:00
  DOI: 10.1111/bmsp.12215
Riemannian Newton and trust‐region algorithms for analytic rotation in
exploratory factor analysis
- Authors: Yang Liu
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-07-26T10:36:25-07:00
  DOI: 10.1111/bmsp.12211
Nested diagnostic classification models for multiple‐choice items
- Authors: Ren Liu; Haiyan Liu
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-07-23T12:00:00-07:00
  DOI: 10.1111/bmsp.12214
Bayesian Gaussian distributional regression models for more efficient norm
estimation
- Authors: Lieke Voncken; Thomas Kneib, Casper J. Albers, Nikolaus Umlauf, Marieke E. Timmerman
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-07-20T11:56:11-07:00
  DOI: 10.1111/bmsp.12206
An exploratory analysis of the latent structure of process data via action
sequence autoencoders
- Authors: Xueying Tang; Zhi Wang, Jingchen Liu, Zhiliang Ying
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-05-22T12:00:00-07:00
  DOI: 10.1111/bmsp.12203
Inferences about which of J dependent groups has the largest robust
measure of location
- Authors: Rand R. Wilcox
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-05-05T12:55:47-07:00
  DOI: 10.1111/bmsp.12205
Stopping rules for multi‐category computerized classification
testing
- Authors: Chun Wang; Ping Chen, Alan Huebner
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-04-02T12:00:00-07:00
  DOI: 10.1111/bmsp.12202
Can we disregard the whole model' Omnibus non‐inferiority testing
for R2 in multi‐variable linear regression and in ANOVA
- Authors: Harlan Campbell; Daniël Lakens
  Abstract: British Journal of Mathematical and Statistical Psychology, EarlyView.
  Citation: British Journal of Mathematical and Statistical Psychology
  PubDate: 2020-02-13T08:39:45-08:00
  DOI: 10.1111/bmsp.12201